The present specification generally relates to technology for visualizing viewer traffic, such as, but not limited to, the viewer traffic of a given show relative to other competing show(s) and/or content provider(s).
Audience measurement systems, such as the audience measurement system provided by Nielsen, are capable of measuring TV viewing behavior by capturing data from national and local meters installed in the homes of a segment of the population and analyzing that data to determine how many people are watching the various shows that are on air. Other solutions measure viewer habits on other platforms, such as web-browsers, mobile apps, over-the-top (OTT) apps, etc.
However, these audience measurement systems, in many aspects, lack the ability to provide convenient virtual tools for analyzing, visualizing, and navigating the data being collected. Rather, the systems often merely provide raw data describing user behavior that is difficult to process for essential information about a show or merely provide standard statistics such as a show's demographic, reach, gross reach, cumulative reach, television rating point (TVR), etc., which often do not provide insights into the actual content of a given show, or the reasons viewers are not watching the show.
In addition, with the advent of the Internet, viewers are increasingly consuming video content online using a variety of different viewing platforms, such as smart phones, web-enabled TVs, tablets, laptops, etc., instead of using traditional broadcasting platforms, such as watching over-the-air television broadcasts. Existing audience measurement systems are unable to monitor all of these different platforms for a number of reasons including that they do not have access to those platforms or the back end systems providing content to those platforms, they are unable to keep up with the current rate of innovation and the diversification of viewing options, they only specialize in or focus on a certain segment (e.g., browser-based video, app-based video, satellite TV, cable TV, over-the-air (OTA) TV, etc.), etc.
As a result, content producers are unable to effectively monitor the performance of their content across the different viewing platforms that are currently available, and in many cases have to guess the reasons why a given show is under or over performing. Furthermore, content producers are unable to conveniently visualize essential information about a given show using existing solutions, such as how many viewers are abandoning a show at various different points of the show, the specific reasons viewers are abandoning a show (e.g., is it because of reasons external to the show, the episode itself or the entire series, certain people on the show, etc.), how a given show stacks up to other shows at different points of time of the show, etc.